Assessing biologic/toxicologic effects of extractables from plastic contact materials for advanced therapy manufacturing using cell painting assay and cytotoxicity screening

Plastic components are essential in the pharmaceutical industry, encompassing container closure systems, laboratory handling equipment, and single-use systems. As part of their material qualification process, studies on interactions between plastic contact materials and process solutions or drug products are conducted. The assessment of single-use systems includes their potential impact on patient safety, product quality, and process performance. This is particularly crucial in cell and gene therapy applications since interactions with the plastic contact material may result in an adverse effect on the isolated therapeutic human cells. We utilized the cell painting assay (CPA), a non-targeted method, for profiling the morphological characteristics of U2OS human osteosarcoma cells in contact with chemicals related to plastic contact materials. Specifically, we conducted a comprehensive analysis of 45 common plastic extractables, and two extracts from single-use systems. Results of the CPA are compared with a standard cytotoxicity assay, an osteogenesis differentiation assay, and in silico toxicity predictions. The findings of this feasibility study demonstrate that the device extracts and most of the tested compounds do not evoke any measurable biological changes on the cells (induction  ≤ 5%) among the 579 cell features measured at concentrations  ≤ 50 µM. CPA can serve as an important assay to reveal unique information not accessible through quantitative structure–activity relationship analysis and vice versa. The results highlight the need for a combination of in vitro and in silico methods in a comprehensive assessment of single-use equipment utilized in advanced therapy medicinal products manufacturing.


Patient exposure
Unique challenges arise when considering the safety of PERLs in AT because various types of exposure must be considered.Patient exposure risks include the PERL exposure to the cells during the ex vivo manipulation and processing, and the direct infusion of the liquid and the cellular phase 7 .A practice to determine PERL exposure, i.e., measurement of trace contaminants adsorbed on cells and/or dissolved in the liquid phase, has not yet been established.An elegant alternative is to model the exposure of PERLs onto the therapeutic cells and the patient using available extractables data of SUS.This approach considers the physical parameters associated with PERL uptake by cells and the specific processing conditions 4,[11][12][13] .There are established concepts for realistic exposure calculations that take into account the sources and sinks of PERLs [14][15][16][17] .These might also be applicable to ATMP manufacturing.However, in AT processes, impurity removal is less efficient and is typically achieved through simple washing steps 7 .
Methods are not yet established to investigate the biological effects of PERLs on therapeutic cells, such as impaired cell proliferation or viability.Budde et al. 18 reported detrimental effects on T-cell growth and loss of potency caused by compounds migrating from plastic materials used in AT applications.Another highly relevant problem expressed by various stakeholders, including authorities, is the formation of degenerated cells due to ex vivo manipulations of cells in the artificial environment of plastics, as associated with SUS.Degenerated cells can lead to critical health issues for the patient, such as tumor formation 19 .

Biocompatibility testing
Several biological tests are used to complement the evaluation for suitability of SUS besides extractables safety assessments.Mandatory tests include USP 〈87〉 and ISO 10993-5 cytotoxicity tests (International Organization for Standards) 20,21 .To address the suitability-for-use of SUS in biopharmaceutical upstream processes, specific cell tests were developed by DECHEMA (Gesellschaft für Chemische Technik und Biotechnologie e.V.) and ASTM (American Society for Testing and Materials).These tests are designed to evaluate the compatibility of SUS with host cells, e.g., Chinese hamster ovary (CHO) cells, for the production of monoclonal antibodies (ASTM E3231-19) 22,23 .
In vivo animal studies can detect a broad spectrum of systemic effects on the tested organism.In contrast, in vitro test systems are very specific but can typically detect only one aspect of a toxicological endpoint.Notably, the relevance of in vivo animal test endpoints to assess ex vivo manipulated human cells in ATMP is questionable; effects measured under in vitro conditions are likely more relevant 24,25 .SI-Table 1 shows common test methods and quality attributes for the qualification of SU materials used as equipment in biopharmaceutical and AT manufacturing.Consideration should also be given to the limited transferability of results to humans and ethical aspects of animal testing (e.g., USP 〈88〉) for safety evaluations in both applications [24][25][26][27][28] .

Toxicological risk assessment
Assessment methods are established for therapeutic biological drugs and pharmaceuticals 6,[29][30][31][32] .A toxicological risk assessment of a compound uses health-based exposure limits, such as the permitted daily exposure (PDE) value in the regulation of pharmaceutical products 33,34 .Similar methods are published for medical devices in the guidance document ISO 10993-17, which uses the term "tolerable intake 35 ".Toxicologists face challenges when extrapolating results from oral studies with animals to parenteral pathways.This is due to the need for careful consideration of appropriate factors for route-to-route extrapolation, taking into account the compounds' bioavailability 29,33 .It is essential to handle this process with care to avoid overlooking significant route-specific effects [36][37][38] .
Nowadays, in vitro studies are widely accepted in regulatory safety testing for the toxicological endpoints of cytotoxicity, skin irritation, eye irritation, skin sensitization, mutagenicity, and the identification of endocrine disruptors 39 .In consequence, multiple in vitro studies with cells are often required to cover one toxicological endpoint-a popular example is skin sensitization 40 .We employ QSAR methods to screen the toxicological properties of tested extractables.This involves analyzing compounds with similar structures through read across information to evaluate the toxicological properties.

Cell painting assay
The Cell Painting assay (CPA) is a high-content and image-based method that measures phenotypic changes in mammalian cells, including human cells, by employing multiplexed fluorescent dyes to stain various cellular components or organelles, allowing the identification of small-molecule bioactivity in perturbed or restored cellular phenotypes 41 .Studying cell morphology offers a visual insight into molecular and physiological processes, reflecting the cell's function, health, differentiation, and response to chemicals, including drugs or contaminations.CPA enables the observation of cellular morphology/phenotype changes and is, therefore, applicable for uncovering biological information about the cellular state and potential perturbations without the need for a prior target hypothesis 42 .It is not limited to a phenotype of interest in a given assay and covers a wide bioactivity space 42,43 .By comparing morphological profiling data from reference compounds with known biological activities, it is feasible to identify biological pathways and modes of action for newly tested compound [43][44][45][46] .
CPA is used in pharmaceutical research to support target identification for drugs 47,48 , and to evaluate humanrelevant toxicity mechanisms with adherent human cells 49,50 .Primary immune cells, such as peripheral blood mononuclear cells (PBMCs), were used to reveal molecular health-associated phenotypes with non-adherent cells 41 .CPA is considered as a useful human-relevant new approach methodology (NAM) and a valuable technology to reduce animal testing.However, it should be supplemented with other NAM and not applied as standalone methodology [51][52][53] .
In our study we used one type of human cells to investigate exemplarily potential effects on human cells used in ATMP processes.The evaluation of several hundreds of cell features is a significant advantage because we assume that most of these features are related to common biological functions and parameters which are relevant for any human cell type.This include morphological integrity, energy production, protein synthesis, reproduction, and cell growth.
However, it is important to note certain limitations of the CPA: • Similar to other cell-based assays, compound stability in the assay system and bioavailability in the cells is required.• Activity in the CPA relies on changes in the cell's morphology.Only compounds acting on targets/pathways whose modulation induces a morphological change will give an observable effect (induction) in the CPA.• Comparing intensities of profiles with low similarity does not allow conclusions about different compound activities since the modulation of different targets may induce different extents of morphological effects.• Although, the implementation of the CPA employed in this study analyzes 579 stable morphological features (see experimental setup of CPA) associated to desired and undesired human cell effects, using just one cell type in this in vitro CPA cannot fully assess effects on all cell types or the entire human body.Testing other cell types and specific parameters that are tailored to each cell type is recommended but would exceed the scope of this feasibility study.

Tested compounds and extracts
Solvents and tested chemicals were of synthesis grade or better.Stock solutions (10 mM) of the test compounds were prepared in dimethyl sulfoxide (DMSO, CAS 67-68-5, Serva, Cat No, 20385).The selected molar concentration range for the CPA is 10 to 50 µM.In total, 45 compounds, including several known extractables, were selected for screening by the CPA.They are provided with information on their application or formation in SI-Table 2. Furthermore, two 50% ethanol extracts from an extraction study of two SU components-a sterilizing-grade filter and silicone tubing-were subjected to the test.The 50% ethanol of the SU filter and tubing contained a mixture of > 20 different extractable compounds with concentrations between 0.1 and up to 2 µg/ml for the filter and up to 11 µg/ml for the tube extract.Leachable concentrations are typically much lower than extractables, making the selected compound concentrations relevant for cell impact investigation.
Comprehensive details on compound selection and extractions are provided also in SI-Table 2. Practical limitations of compound selection arise from the requirement that the compounds must be accessible to the cells, i.e., can be extracted and dissolved in the media.Therefore, almost all compounds tested have a log P ≤ 5. log P is the logarithm of the partition coefficient between water and octanol (K o/w ).

Experimental setup of CPA
The assay follows closely the method described by Bray et al. 43 Initially, 5 µL U2OS medium were added to each well of a 384-well plate (PerkinElmer CellCarrier-384 Ultra).Subsequently, U2OS cell were seeded with a density of 1600 cells per well in 20 µL medium.The plate was incubated for 10 min at room temperature (RT), followed by an additional 4 h incubation (37 °C, 5% CO 2 ).Compound treatment was performed with the Echo 520 acoustic dispenser (Labcyte) at final concentrations of 50, 30, or 10 µM and, if necessary, at lower concentrations.Incubation with compound was performed for 20 h (37 °C, 5% CO 2 ).Subsequently, mitochondria were stained with Mito Tracker Deep Red (Thermo Fisher Scientific, Cat.No. M22426).The Mito Tracker Deep Red stock solution (1 mM) was diluted to a final concentration of 100 nM in prewarmed medium.The medium was removed from the plate leaving 10 µL residual volume and 25 µL of the Mito Tracker solution were added to each well.The plate was incubated for 30 min in darkness (37 °C, 5% CO 2 ).To fix the cells, 7 µl of 18.5% formaldehyde in PBS were added, resulting in a final formaldehyde concentration of 3.7%.Subsequently, the plate was incubated www.nature.com/scientificreports/for another 20 min in darkness (RT) and washed three times with 70 µL of PBS (Biotek Washer Elx405).Cells were permeabilized by addition of 25 µL 0.1% Triton X-100 to each well, followed by 15 min incubation (RT) in darkness.The cells were washed three times with PBS leaving a final volume of 10 µL.To each well 25 µL of a staining solution were added, which contains 1% BSA, 5 µL/mL Phalloidin (Alexa594 conjugate, Thermo Fisher Scientific, A12381), 25 µg/ml Concanavalin A (Alexa488 conjugate, Thermo Fisher Scientific, Cat.No. C11252), 5 µg/ml Hoechst 33342 (Sigma, Cat.No. B2261-25 mg), 1.5 µg/ml WGA-Alexa594 conjugate (Thermo Fisher Scientific, Cat.No. W11262) and 1.5 µM SYTO 14 solution (Thermo Fisher Scientific, Cat.No. S7576).The plate is incubated for 30 min (RT) in darkness and washed three times with 70 µL PBS.After the final washing step, the PBS was not aspirated.The plates were sealed and centrifuged for 1 min at 50 × g.The plates were prepared in triplicates with shifted layouts to reduce plate effects and imaged using a Micro XL High-Content Screening System (Molecular Devices) as shown in Figure 1.
The images generated were processed with the CellProfiler package (https:// cellp rofil er.org/, version 3.0.0)on a computing cluster of the Max Planck Society to extract 1716 cell features per microscope site.The data was further aggregated as medians per well (9 sites → 1 well), then over the three replicates.
Out of the initial 1716 features, a subset of 579 highly reproducible and robust features was determined using a procedure based on the criteria described by Woehrmann et al. 54 Two biological repeats of one plate containing reference compounds were analysed.For every feature, its full profile over each whole plate was calculated.If the profiles from the two repeats showed a similarity ≥ 0.8 (see below), the feature was added to the set.This procedure was performed once and served as the basis for all subsequent analyses.
The phenotypic profiles were compiled from the Z-scores of all individual cellular features, where the Z-score is a measure of how far away a data point is from a median value.
Specifically, Z-scores of test compounds were calculated relative to the Median of DMSO controls.Thus, the Z-score of a test compound defines how many MADs (Median Absolute Deviations) the measured value is away from the Median of the controls as illustrated by the following formula: The phenotypic compound profile is then determined as the list of Z-scores of all features for one compound and is visualized via heatmap (examplarily see Fig. 2).
In addition to the phenotypic profile, an induction value was determined for each compound as the fraction of significantly changed features, in percent:  where x is the mean of the elements of x , x • y is the dot product of x and y , and x 2 is the Euclidean norm of x: The biosimilarity is then defined as: Biosimilarity is expressed as a percentage (0-100), and values smaller than 0 are set to 0.
In addition to calculating biosimilarity between the full morphological profiles of two Cell painting measurements, Pahl et al. 44 developed an approach to assign similarity to biological clusters by comparing sub-profiles.
In essence, a set of 12 biological clusters was defined from Cell painting measurements with confirmed activity on these clusters.By considering only the features with similar values from the group of measurements for each cluster, a representative median profile was calculated for each cluster.These representative median profiles are of different length and shape for each cluster (Fig. 3).This experimental setup represents a proven practice when performing CPAs to detect morphological changes of adherent human U2OS cells using a serum-containing defined cell culture medium 55,56 .Possible quenching effects with the used dyes in the CPA are considered of low concern because the fluorescent dyes are not in contact with the tested compounds during incubation.

Osteogenesis inhibition assay (OIA)
The osteogenesis inhibition assay was performed as described elsewhere 57 .Briefly, murine mesodermal stem cells (C3H10T1/2) were stimulated with purmorphamine (a Hedgehog agonist) to induce the expression of the osteogenesis marker alkaline phosphatase.After treatment with compounds for 96 h, the expression of alkaline phosphatase was quantified using a luminogenic substrate (CDP-Star, Roche), which reveals whether a compound is a developmental pathway inhibitor of, e.g., the Hedgehog (Hh) signaling pathway or other related pathways.

Cytotoxicity testing with CHO cells
An IgG1-producing Chinese hamster ovary (CHO) cell line (CHO DG44 from Sartorius Stedim Cellca GmbH, Germany) was cultivated in chemically defined media (ActiCHO SM, Cytiva, USA).The cell line was adapted to grow in suspension without animal-derived supplements.Spiking experiments were carried out after cultivation as described elsewhere 58 .This method determines effective concentrations (EC 50 ) that cause 50% inhibition of cell growth.Data evaluation was carried out according to the method described in ASTM E3231-19, "Standard Guide for Cell Culture Growth Assessment of Single-Use Material 23 ".This test defines best practices using serumfree, chemically-defined cell culture medium to prevent false negative results.

QSAR analysis
The software "Vega 1.2.0" (www.vegah ub.eu/) was used for the prediction of mutagenicity (Ames test) by QSAR analysis.The software "QSAR Toolbox 4.5" (https:// qsart oolbox.org) gathered experimental toxicological data such as in vitro genotoxicity studies and made predictions of toxicity using 15 models with different prediction profiles for protein binding and deoxyribonucleic acid (DNA) alerts, mutagenicity, and irritation (https:// qsart oolbox.org).The selected models are suitable to reveal structure motifs suspected to form covalent modifications of proteins or DNA, posing a significant risk in AT and other biopharmaceutical processes.Li et al. 6 give examples of such structures.The toxic hazard classification by Cramer may also indicate such risks 59 .

Cell painting assay
We tested compounds which are primarily extractables of SUS one can expect in aqueous solutions, e.g.used in biopharmaceutical or in ATMP processes.Most of the examined compounds did not show any significant effect on the 579 morphological features evaluated at concentrations exceeding those encountered in extractables studies of SU devices.We consider compounds with an induction ≥ 5% active in the CPA 44 .Remarkably, only a limited subset comprising 4 out of 45 extractable substances demonstrated an induction level surpassing the predefined 5% threshold in the context of the assessed human cells.The results are summarized in Table 1.The four compounds are an antistatic agent N-lauryldiethanolamine, an antioxidant degradant bis(2,4-di-tert-butylphenyl) phosphate (bDtBPP) known for its cell growth inhibition, a starting material for non-ionic surfactants or antioxidants 4-n-nonylphenol, and a photoinitiator diphenyl(2,4,6-trimethylbenzoyl)phosphine oxide (TPO).The two organic extraction solutions of the sterilizing-grade filter and the silicon tubing consisting of approximately (approx.) 20 extractables showed no effect in the CPA.
N-Lauryldiethanolamine was the only compound with a strong inhibitory effect on cell growth, starting from 30 µM.An induction of 61% was found at the lowest test concentration of 3 µM (additional lower concentration Table 1.CPA and osteogenesis inhibition assay results.CPA for the four extractables showing an induction > 5%.Induction in CPA describes the bioactivity of the compound and is defined as the percentage of altered features compared to the controls.Highest Similarity to Biological Clusters is the assignment of the compound to reference compounds with a confirmed biological activity based on similarities in cluster features 44 .Cell Count is the ratio of the number of detected cells in the test sample and the number of cells in the control sample in which the cells divide once within the incubation time of 20 h.A cell count of 50% means a cell arrest was observed: no cell division took place in the test sample.The relative cell count can be considered as the sum of different effects that may end up and result in growth inhibition.Osteogenesis Inhibition Assay is the half maximal inhibitory concentration (IC 50 ) describes an inhibitory effect to a specific function, e.g., alkaline phosphatase expression and is tested with the osteogenesis inhibition assay.It was performed for all tested compounds.

Osteogenesis inhibition assay [IC50]
N-Lauryldiethanolamine 61 ( www.nature.com/scientificreports/tested) with a predicted effect on cholesterol homeostasis.Cholesterol homeostasis describes processes that maintain a steady state level of cholesterol in the cells.Furthermore, the compound shows some lysosomotropic behavior at 30 µM.Lysosomotropic active compounds do not have a designated target in the cell but rather migrate into the cellular lysosome due to a weak alkaline nature 46,60 .Upon protonation within the lysosome, the molecules cannot escape and accumulate, resulting in a lysosomal burst triggering apoptotic signaling.Drugs with a log P > 2 and pKa between 6.5 and 11 commonly cause lysosomal accumulation (N-Lauryldiethanolamine: calc.log P: 3.2, calc.pKa 9.2) 61 .Morphological profiling has captured small morphological changes upon a given perturbation before it reaches toxic levels.N-Lauryldiethanolamine was toxic at a concentration of ≥ 10 µM in the osteogenesis inhibition assay and excluded from further dose-response measurement.
The compounds bDtBPP, 4-n-nonylphenol, and TPO show inductions below 20%.Fortunately, these three active compounds are commonly not linked to SU construction materials nowadays, or their level is reduced and controlled (e.g., bDtBPP) 62 .Compounds bDtBPP and 4-n-nonylphenol show low similarity to the DNA synthesis cluster, and TPO shows medium similarity to the histone deacetylase (HDAC) cluster.TPO also showed a lysosomotropic behavior in line with a log P > 2 (TPO: calc.log P: 4.8).Surprisingly, bDtBPP revealed no impact on cell growth for the U2OS cells (see next chapter).Subsequent analysis in the osteogenesis inhibition assay revealed that three of the four compounds inhibit the osteogenesis pathway.
Figure 4 shows microscopic images of the cell organelles after treatment with N-Lauryldiethanolamine or bDtBPP compared to the control sample (DMSO).When examining the images, N-Lauryldiethanolamine differs significantly from the control, which cannot be easily recognized for bDtBPP.Based on this visual analysis, it is apparent that these two substances have different profiles.The automated image analysis carried out for CPA reveals the distinct profiles (Fig. 5), with the one for N-Lauryldiethanolamine being more intense than those for the other three compounds In Fig. 4 the measured features are assigned to the compartments defined by CellProfiler using the five imaged channels.
During CPA evaluation the cellular compartments are imaged in five different channels.In Fig. 6, the percentage of changed features that depend on individual channels is shown.In addition, the figure contains the changed features for the AreaShape group.The channels related to the endoplasmic reticulum (ER) and nuclei (Hoechst) experience the highest degree of change for the four CPA active compounds.The percentage of changed features is above 40% with the exception of TPO with approx.5% for nuclei.N-Lauryldiethanolamine induced at the concentration of 3 µm a percentage of changed features of approx.50 to 90% for all channels.The channels for mitochondria (Mito), golgi/cell membrane/cytoskeleton-compartments (Ph_golgi), and cytoplasmic RNA/ nucleoli are changed by the other three compounds below 20%.The AreaShape group is related to the shape of the cells.N-Lauryldiethanolamine changed all features related to this group, and bDtBPP or TPO changed approx.20 or 30% of the features, respectively.

Comparison of CPA results with CHO toxicity testing data
Toxicity testing of selected extractables has been carried out with a commonly used CHO cell line according to ASTM E3231-19 to assess the potential impact of these compounds on biopharmaceutical cell culture performance.Table 2 summarizes the results of spiking experiments using an antibody-secreting CHO DG44 cell line with extractables that showed activity in the CPA.In contrast to the CPA, experiments were carried out without serum supplementation and in chemically defined cultivation medium to sensitively detect the endpoint cell growth.Compared to the U2OS cell line used in the CPA, the CHO cell line with the given test

Summary and conclusion
This feasibility study highlights the importance of comprehensive biocompatibility testing for SUS in biopharmaceutical and ATMP manufacturing.The CPA and cytotoxicity screening conducted on the human U2OS, and CHO cell lines provided valuable insights into the biological effects of plastic-related chemicals, particularly extractables that could potentially leach into pharmaceutical products.
The results showed that most of the 45 tested extractables did not significantly affect the morphological features of the cells at concentrations relevant to SUS.However, a subset of compounds, including N-Lauryldiethanolamine, bis(2,4-di-tert-butylphenyl)phosphate (bDtBPP), 4-n-nonylphenol, and diphenyl(2,4,6trimethylbenzoyl)phosphine oxide (TPO), demonstrated biological activity in the CPA.These findings were further supported by cytotoxicity testing with CHO cells, which confirmed the potential risks of three of these compounds.QSAR tools were used to screen for toxicological alerts, such as mutagenicity, revealing that results from QSAR analysis do not always correlate with the observed biological activity.This highlights the need for a combination of in vitro and in silico methods for a comprehensive assessment.Consequently, compounds identified to show cytotoxic effects in in vitro test assays should be avoided or, at least, their quantity should be reduced and controlled in plastics used for SU equipment or ancillary materials in ATMP manufacturing 62 .
In conclusion, the integration of CPA with existing tools, such as cytotoxicity testing and QSAR analysis, offers a promising approach to support the evaluation of the biocompatibility of materials used in SUS.The findings emphasize the necessity for careful selection and qualification of single-use devices to ensure patient safety and product quality in biopharmaceutical and ATMP processes.The tested compounds should be extended for extractables or extracts of other contact materials which were not part of this feasibility study, for example polyvinyl chloride (PVC) used as material for tubing in ATMP processes.
The study also shows the need for the continued development and refinement of testing methods to better predict and mitigate the risks associated with process equipment-related leachables.This includes creating realistic exposure scenarios in ATMP processes for both cells and patients 13 .To establish a toxicity screening test based on the CPA, a set of tests comprising various differentiated cell lines is required 18 .These test scenarios should cover not only common cell features but also specific cell features that are relevant for differentiated cells in ATMP.However, this approach goes beyond the scope of this feasibility study.

Figure 2 .
Figure 2. Above: An example for two compounds with highly similar profiles (96% biosimilarity); below: An example for two compounds with low similarity profiles (0% Biosimilarity): In each case, colored bands represent the Z-scores of individual features.

Figure 3 .
Figure3.List of currently identified clusters and their median profiles.By comparing the median cluster profiles to the matching sub-profiles of measured compounds (only profiles of the same length can be compared for similarity), a biosimilarity to each cluster can be calculated.

Figure 5 .Figure 6 .
Figure 5. Heatmap of compounds (with molarity) active in the CPA showing scored cell profiles from 579 features.Each colored band represents one Z-score of a feature.Blue color: decreased feature, red color: increased feature.